Detection of a methanol megamaser in a major-merger galaxy

We have detected emission from both the 4_{-1}-3_{0} E (36.2~GHz) class I and 7_{-2}-8_{-1} E (37.7~GHz) class II methanol transitions towards the centre of the closest ultra-luminous infrared galaxy Arp 220. The emission in both the methanol transitions show narrow spectral features and have luminosities approximately 8 orders of magnitude stronger than that observed from typical class I methanol masers observed in Galactic star formation regions. The emission is also orders of magnitude stronger than the expected intensity of thermal emission from these transitions and based on these findings we suggest that the emission from the two transitions are masers. These observations provides the first detection of a methanol megamaser in the 36.2 and 37.7 GHz transitions and represents only the second detection of a methanol megamaser, following the recent report of an 84 GHz methanol megamaser in NGC1068. We find the methanol megamasers are significantly offset from the nuclear region and arise towards regions where there is Ha emission, suggesting that it is associated with starburst activity. The high degree of correlation between the spatial distribution of the 36.2 GHz methanol and X-ray plume emission suggests that the production of strong extragalactic class I methanol masers is related to galactic outflow driven shocks and perhaps cosmic rays. In contrast to OH and H2O megamasers which originate close to the nucleus, methanol megamasers provide a new probe of feedback (e.g. outflows) processes on larger-scales and of star formation beyond the circumnuclear starburst regions of active galaxies.Comment: Accepted for publication in ApJ

Pulmonary alveolar type I cell population consists of two distinct subtypes that differ in cell fate.

Pulmonary alveolar type I (AT1) cells cover more than 95% of alveolar surface and are essential for the air-blood barrier function of lungs. AT1 cells have been shown to retain developmental plasticity during alveolar regeneration. However, the development and heterogeneity of AT1 cells remain largely unknown. Here, we conducted a single-cell RNA-seq analysis to characterize postnatal AT1 cell development and identified insulin-like growth factor-binding protein 2 (Igfbp2) as a genetic marker specifically expressed in postnatal AT1 cells. The portion of AT1 cells expressing Igfbp2 increases during alveologenesis and in post pneumonectomy (PNX) newly formed alveoli. We found that the adult AT1 cell population contains both Hopx+Igfbp2+ and Hopx+Igfbp2- AT1 cells, which have distinct cell fates during alveolar regeneration. Using an Igfbp2-CreER mouse model, we demonstrate that Hopx+Igfbp2+ AT1 cells represent terminally differentiated AT1 cells that are not able to transdifferentiate into AT2 cells during post-PNX alveolar regeneration. Our study provides tools and insights that will guide future investigations into the molecular and cellular mechanism or mechanisms underlying AT1 cell fate during lung development and regeneration

A Survey of Multimodal Information Fusion for Smart Healthcare: Mapping the Journey from Data to Wisdom

Multimodal medical data fusion has emerged as a transformative approach in smart healthcare, enabling a comprehensive understanding of patient health and personalized treatment plans. In this paper, a journey from data to information to knowledge to wisdom (DIKW) is explored through multimodal fusion for smart healthcare. We present a comprehensive review of multimodal medical data fusion focused on the integration of various data modalities. The review explores different approaches such as feature selection, rule-based systems, machine learning, deep learning, and natural language processing, for fusing and analyzing multimodal data. This paper also highlights the challenges associated with multimodal fusion in healthcare. By synthesizing the reviewed frameworks and theories, it proposes a generic framework for multimodal medical data fusion that aligns with the DIKW model. Moreover, it discusses future directions related to the four pillars of healthcare: Predictive, Preventive, Personalized, and Participatory approaches. The components of the comprehensive survey presented in this paper form the foundation for more successful implementation of multimodal fusion in smart healthcare. Our findings can guide researchers and practitioners in leveraging the power of multimodal fusion with the state-of-the-art approaches to revolutionize healthcare and improve patient outcomes.Comment: This work has been submitted to the ELSEVIER for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Bis(μ-2,2′-oxydibenzoato-κ4 O,O′:O′′,O′′′)bis­[(4,4′-dimethyl-2,2′-bipyridine-κ2 N,N′)zinc(II)] dihydrate

In the title compound, [Zn2(C14H8O5)2(C12H12N2)2]·2H2O, the ZnII atom exhibits a distorted octa­hedral coordination geometry, defined by two N atoms from one 4,4′-dimethyl-2,2′-bipyridine ligand and four O atoms from two bridging 2,2′-oxydibenzoate ligands. The mol­ecule is a centrosymmetric dimer. π–π Stacking inter­actions are observed between the 4,4′-dimethyl-2,2′-bipyridine ligands, with a centroid–centroid distance of 3.649 (2) Å